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Math 315 (Methods in Applied Statistics)

According to the syllabus, MATH 315 (Methods in Applied Statistics) “is designed to enable students to develop familiarity with various parametric and nonparametric tests and to gain the knowledge and skills needed to apply statistical concepts to solve applied problems.” In this course “students will learn the logic, the procedures, and the use of common statistical techniques using one of the most commonly used statistical packages – SPSS for Windows.” For those unfamiliar with SPSS, it is a popular software used to analyse data. Students who want to enroll into this course “must lease the statistical package: IBM® SPSS® Statistics Standard GradPack 22 (or higher) from a reliable source.” The prerequisites for MATH 315 include MATH 215, MATH 216, MGSC 301, SOCI 301, or any equivalent introductory quantitative statistical methods course.

Methods in Applied Statistics consists of seven units, six tutor marked assignments, one midterm exam, and one final exam. The first unit is an introduction to research design concepts. The second focusses on nonparametric tests. The third unit covers the analysis of variance and multiple comparison procedures, while unit four consists of simple linear regression and correlation. The fifth unit covers multiple linear regression and the general linear model. Unit six expands on unit three with one-way analysis of variance for completely randomized designs. Lastly, unit seven covers analysis of variance for blocked designs. The six assignments, weighing five percent each, cover the seven units. The midterm, weighing thirty percent, covers the topics discussed in the first three tutor marked assignments; meanwhile, the final exam, weighing forty percent, is non-cumulative and covers the topics discussed in the final three tutor marked assignments. For the midterm and final exam students are allowed one double-sided written or printed cheat sheet and a non-programmable calculator.

Upon completing this course, students will have “an in-depth knowledge of basic statistical principles, a basic understanding of experimental design, proficiency in the analysis of a wide range of data sets selected from the biological, physical, social sciences, and from business applications, and gain skill with a wide range of statistical tests, including correlation, simple and multiple linear regression models, single and two factor analyses of variance, and logistic regression.”

Dr. Thomas Varghese, Subject Matter Expert (SME) and a tutor for MATH 215, MATH 216, and MATH 315, stated “statistics and statistical expertise is needed in virtually any field of human activity, whether it is medicine, natural science, engineering, agriculture, business, industry or government sector, for efficient decision making. Hence, we introduced a second course which is a continuation of MATH 215 / MATH 216.”

Varghese continues, “the main goal of this course is to give students a comprehensive knowledge of the commonly used statistical techniques and its practical application in data analysis, using SPSS for windows. Throughout this course, students will gain the knowledge and skills needed to conduct and evaluate a research study.”

He adds, “the level of mathematical knowledge required for this course is kept minimal as the focus of this course is on statistical practice rather than the theory. This approach will attract students from non-mathematics majors as well.”

Lastly, Varghese states “MATH 315 is of considerable value to those who plan to take any courses for which collection and analysis of data are the key requirements. Furthermore, it is a pre-requisite for those who plan to major in statistics, business, agriculture, biology, and many other areas which require quantitative reasoning. This course is very useful to those who plan a graduate study in which some sort of data collection and quantitative analysis is a requirement.”

Whether MATH 315 is a degree requirement of yours or the topics above interest you, this course will have you learning a lot of useful skills, such as efficient decision making, data collection, and quantitative analysis that will further assist you in other courses and in real life scenarios. For more information on this course, visit MATH 315’s online syllabus.